Book Image

Data Exploration and Preparation with BigQuery

By : Mike Kahn
Book Image

Data Exploration and Preparation with BigQuery

By: Mike Kahn

Overview of this book

Data professionals encounter a multitude of challenges such as handling large volumes of data, dealing with data silos, and the lack of appropriate tools. Datasets often arrive in different conditions and formats, demanding considerable time from analysts, engineers, and scientists to process and uncover insights. The complexity of the data life cycle often hinders teams and organizations from extracting the desired value from their data assets. Data Exploration and Preparation with BigQuery offers a holistic solution to these challenges. The book begins with the basics of BigQuery while covering the fundamentals of data exploration and preparation. It then progresses to demonstrate how to use BigQuery for these tasks and explores the array of big data tools at your disposal within the Google Cloud ecosystem. The book doesn’t merely offer theoretical insights; it’s a hands-on companion that walks you through properly structuring your tables for query efficiency and ensures adherence to data preparation best practices. You’ll also learn when to use Dataflow, BigQuery, and Dataprep for ETL and ELT workflows. The book will skillfully guide you through various case studies, demonstrating how BigQuery can be used to solve real-world data problems. By the end of this book, you’ll have mastered the use of SQL to explore and prepare datasets in BigQuery, unlocking deeper insights from data.
Table of Contents (21 chapters)
Free Chapter
1
Part 1: Introduction to BigQuery
4
Part 2: Data Exploration with BigQuery
10
Part 3: Data Preparation with BigQuery
14
Part 4: Hands-On and Conclusion

Using Workbench notebook instances in Vertex AI

This section provides an overview of the notebooks available in Google Cloud and their significance in relation to data exploration and preparation in BigQuery. Workbench notebooks are a powerful component of the Vertex AI platform, enabling data analysts and data scientists to perform data exploration within a collaborative and unified environment. Workbench notebooks are a JupyterLab VM-based offering that can be configured for specific usage scenarios. Let’s discuss this data exploration tool in more detail.

Workbench notebooks provide a unified interface, where data analysts and scientists can work seamlessly on projects. Multiple team members can collaborate on the same notebook, making it easy to share insights, exchange ideas, and work toward data goals. Vertex AI Workbench (https://cloud.google.com/vertex-ai-workbench) offers two types of notebook options, managed notebooks with built-in integrations, and user-managed...